# -*- coding: utf-8 -*-
"""
@author: quincyqiang
@software: PyCharm
@file: gen_feas.py
@time: 2020/9/2 23:36
@description：
"""
import warnings
from datetime import datetime

import numpy as np
import pandas as pd
from sklearn.preprocessing import LabelEncoder
# import nltk
# from nltk.corpus import stopwords
from tqdm import tqdm
import pandas as pd
import numpy as np



train=pd.read_pickle('../user_data/train.pkl')
test=pd.read_pickle('../user_data/test.pkl')


no_fea = ['id', 'label', 'ID', 'fold',
          ]
features = [fea for fea in train.columns if fea not in no_fea]
print(train[features].shape)
print(len(features), features)
def load_data():
    return train, train['label'], test, features
